PROJECT SUMMARY/ABSTRACT: Sarcoidosis is a granulomatous disease of unknown etiology that affects the lungs in 90% of patients resulting in significant morbidity and mortality. The disease has variable outcomes including persistent and/or progressive and remitting disease, and there are no reliable or validated clinical tools available to predict these outcomes. The goal of this study is it investigate changes in bronchoalveolar lavage (BAL) CD4+ T cell phenotype and specific T cell lineage gene expression prospectively to understand the role of Th17.1 and Treg cells with disease course. We will expand upon our novel findings that the most prevalent T effector cell in sarcoidosis lung lavage are Th17.1 cells, capable of significant interferon? (IFN?) production (and may be a source of additional mediators yet undefined). We also found that the abundance of Th17.1 cells were inversely proportional to Treg cells, so that the highest frequencies of Th17.1 and the lowest frequencies of Treg cells were found in patients with advanced disease. Our hypothesis is that the dynamic relationship of multiple T cell effector lineages (Th1, Th17, Th17.1, Treg cells) affects the variable pathobiology and outcomes in sarcoidosis. We hypothesize that sarcoidosis subjects with remitting disease have a decrease in BAL Th17.1 cells and increase in Treg cells over time. This is accompanied by dynamic changes in the transcriptional signatures of the T cell lineages, which regulate their activity and plasticity. Using a longitudinal bronchoscopy study design that has not been undertaken in sarcoidosis, we will prospectively enroll recently diagnosed sarcoidosis subjects and sample BAL cells at two time-points to address our aims. Aim 1 will examine T cell lineage diversity changes during sarcoidosis pathogenesis longitudinally in subjects with progressive vs. remitting disease. In paired lung and blood samples, we will use multi-parameter flow cytometry analysis to compare the frequencies of Th1, Th17, Th17.1, and Treg cells with clinical course (PFTs, chest x-ray, organ involvement). In Aim 2, we will analyze alterations of T cell lineage activity during sarcoidosis pathogenesis via genome wide transcriptional profiles of isolated Treg, Th17, Th17.1 and Th1 cells using low-input RNA- sequencing. Flow sorted lung T cell populations will be used for low-input RNA-seq to compare longitudinal changes to transcriptional signatures between T lineages cells with clinical course. Next, paired total lung and blood RNA-seq analysis will be compared to identify overlapping signatures, which correlate with disease outcomes. In aim 3, we will construct computational tools from T cell lineage diversity and gene expression data to define and/or predict sarcoidosis endotypes using bioinformatic deconvolution and biostatistical methods. The coupling of clinical, genomic and bioinformatic analysis will identify cellular and transcriptional patterns that can be used to define novel sarcoidosis endotypes. These endotypes may impact future therapeutic trials targeting specific cells in the immune response to achieve disease remission.